The effect of the Internet on decision-making during pregnancy: a systematic review.
Ayşe TaştekinSelma İnfal KesimPublished in: Archives of women's mental health (2020)
The purpose of this review is to explain how the Internet affects decision-making in pregnancy. A systematic review was carried out in accordance with the guidelines developed by the National Institute of Health Research at York University. The PubMed, EBSCOhost, Ulakbim Medical Database, Turkish Medline, Web of Science, and Scopus databases were scanned. Three keywords in the titles, abstracts, and keywords of the articles were searched for in the Medical Subject Headings: "Pregnancy," "Decision-making," and "Internet." A total of 1143 articles were found in the first screening. Duplicate articles were removed. The remaining articles were reviewed according to the inclusion criteria. Only articles about healthy pregnant women were accessed, and only full-text research articles published in English were used. Seventeen articles met the inclusion criteria. The sample size varied between 9 and 7092. Most studies reported that pregnant women use the Internet as a source of information about pregnancy. Pregnancy, development of the fetus, labor, neonatal health, and nutrition were the subjects most researched. It was found that women with a higher education, who were young, nulliparous, and primigravid, looked for more information on the Internet. The Internet affects decisions about the type of delivery, drug use in pregnancy, and physical activity. Using the Internet had a positive effect on the decision-making processes of pregnant women, increased their awareness, and had a visible effect on this process.
Keyphrases
- health information
- pregnant women
- pregnancy outcomes
- decision making
- healthcare
- preterm birth
- physical activity
- social media
- public health
- randomized controlled trial
- emergency department
- mental health
- risk assessment
- systematic review
- middle aged
- clinical practice
- smoking cessation
- depressive symptoms
- big data
- machine learning